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Moments are summaries of random variables' characteristics (e.g., location, scale). Use also for fractional moments.
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Link between moment-generating function and characteristic function
$, I can find all the moments of the distribution for the random variable X.
The characteristic function is defined as:
$$
\varphi_X(t) = E(\exp(itX)) = 1 + \frac{it E(X)}{1} - \frac{t^2 E(X^2)}{2!} … I see that $i^2 = -1$ and thus we don't have only $+$ in the characteristic function, but why do we need to subtract moments in the characteristic function? What's the mathematical idea? …